Developing Multi-Database Mining Applications

Information systems and intelligent knowledge processing are playing an increasing role in business, science and technology. Recently, advanced information systems have evolved to facilitate the co-evolution of human and information networks within communities. These advanced information systems use various paradigms including artificial intelligence, knowledge management, and bioinformatics, as well as conventional information processing paradigms.

This research-oriented series publishes books on new designs and applications of advanced information and knowledge processing concepts. Books in the series have a strong focus on information processing combined with, or extended by, new results from adjacent sciences.

Multi-database mining is recognized as an important and strategic area of research in data mining. The authors discuss the essential issues relating to the systematic and efficient development of multi-database mining applications, and present approaches to the development of data warehouses at different branches, demonstrating how carefully selected multi-database mining techniques contribute to successful real-world applications

In showing and quantifying how the efficiency of a multi-database mining application can be improved by processing more patterns, the book also covers other essential design aspects. These are carefully investigated and include a determination of an appropriate multidatabase mining model, how to select relevant databases, choosing an appropriate pattern synthesizing technique, representing pattern space, and constructing an efficient algorithm. The authors illustrate each of these development issues either in the context of a specific problem at hand, or via some general settings.

Developing Multi-Database Mining Applications will be welcomed by practitioners, researchers and students working in the area of data mining and knowledge discovery.